Cloud DevOps Engineer

Job Description

Job Description

We are hiring for a Senior DevOps / Site Reliability Engineer – AI Platform. The role focuses on building, operating, monitoring, and scaling an enterprise AI platform across Development, QA, and Production environments.
A strong fit will have advanced Azure and Kubernetes experience along with strong expertise in observability, dashboards, monitoring, alerting, and automated scaling.

What you bring

• Strong professional experience in DevOps, Site Reliability Engineering, cloud infrastructure, or platform engineering.
• Advanced hands-on experience with Microsoft Azure.
• Strong experience deploying and operating Kubernetes environments.
• Strong knowledge of Docker and containerization technologies.
• Experience supporting containerized applications across Development, QA, and Production environments.
• Advanced experience designing and building dashboards using Grafana, Kibana, Azure Monitor, Application Insights, or comparable tools.
• Strong experience with monitoring, observability, logging, alerting, and operational health checks.
• Experience with application load, infrastructure capacity, performance, and automated scaling.
• Experience with CI/CD pipelines and automated application deployment.
• Experience with Infrastructure as Code tools such as Terraform, Bicep, or ARM templates.
• Strong troubleshooting skills across applications, containers, infrastructure, networking, and cloud services.

What you'll do

• Design, deploy, configure, and maintain infrastructure within Microsoft Azure.
• Deploy and operate containerized applications using Kubernetes.
• Monitor container and cluster health, resource consumption, capacity, and performance.
• Configure scaling policies and develop intelligent scaling approaches based on workload and resource utilization.
• Design and build operational dashboards covering platform health, performance, capacity, errors, latency, and container health.
• Implement monitoring and alerting across infrastructure, applications, containers, integrations, and AI platform services.
• Establish actionable alerts, health checks, anomaly detection, and automated remediation where appropriate.
• Support production platform stability, availability, and operational readiness.
• Investigate platform, deployment, infrastructure, monitoring, and performance issues.
• Participate in root-cause analysis and implement preventative improvements.
• Create operational runbooks and troubleshooting guidance.

Nice to have

• Experience supporting AI, machine learning, data, or high-compute platforms.
• Experience monitoring AI models, inference services, token usage, GPU workloads, API consumption, queues, or model performance.
• Experience implementing automated remediation, predictive monitoring, or AI-assisted platform operations.
• Familiarity with AWS services and cloud operations.
• Experience with Elasticsearch, Log Analytics, OpenTelemetry, Prometheus, or similar observability technologies.
• Experience defining service-level indicators, service-level objectives, and reliability standards.
• Experience with security, identity, secrets management, and cloud governance within Azure.